New Molecular Tool for Prognosis and Treatment of Brain Tumors

In a paper recently published in BMC Medical Genomics, scientists from Sandra L Rodriguez-Zas’ lab at the University of Illinois have identified a cohort of biomarkers that help predict survivability of patients who are afflicted with the aggressive malignant Glioblastoma multiforme brain tumor. The study also found that survivability varies between different genetic profiles and that factors such as race, gender and therapy may have a significant impact upon the survival and quality of life of individuals afflicted by glioblastoma multiforme.

As is evident from figure 4 of the paper, (see below), the network of gene associations in this form of brain cancer is quite complex. Nonetheless, analysis of multiple gene expression profiles in combination with clinical variables was proven to be an effective tool to accurately predict three predefined glioblastoma survival variables. More specifically, the study shows which cluster of genes are associated with long-term survivability, which genes are associated with disease progression and which genes are associated with progression-free survival (and whether these genes need to be up or downregulated for such survival to occur).

Figure 4. Gene network from the functional analysis of lifetime glioblastoma survival.

What is most unique about this study is how it factors in variables such as age and race into the equation and concludes that gene expression patterns alone are most useful as prognostic indicators when used in consideration with age and race as well. As the authors mention in the discussion,

this study demonstrated the preeminence of developing multigene prognostic indices of glioblastoma survival through the integration of variable selection and survival models relative to the simple-yet- simplistic single-gene analysis.

According to lead author Nicola Serao:

Our research suggests you can’t treat all patients the same. For example, we found gene expression patterns that have different, and sometimes opposite, relationships with survival in males and females and concluded that treatments affecting these genes will not be equally effective. Personalized therapy dependent on gender, race and age is something that is possible today with our advanced genomic tools.


SerĂ£o NV, Delfino KR, Southey BR, Beever JE, & Rodriguez-Zas SL (2011). Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival. BMC medical genomics, 4 PMID: 21649900

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